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Skills available for Indiana Algebra 1 standards

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AI.RNE Real Numbers and Expressions

AI.F Functions

AI.L Linear Equations, Inequalities, and Functions

AI.SEI Systems of Equations and Inequalities

AI.QE Quadratic and Exponential Equations and Functions

AI.DS Data Analysis and Statistics

  • AI.DS.1 Distinguish between random and non-random sampling methods, identify possible sources of bias in sampling, describe how such bias can be controlled and reduced, evaluate the characteristics of a good survey and well-designed experiment, design simple experiments or investigations to collect data to answer questions of interest, and make inferences from sample results.

  • AI.DS.2 Graph bivariate data on a scatter plot and describe the relationship between the variables.

  • AI.DS.3 Use technology to find a linear function that models a relationship for a bivariate data set to make predictions; interpret the slope and y-intercept, and compute (using technology) and interpret the correlation coefficient.

  • AI.DS.4 Distinguish between correlation and causation.

  • AI.DS.5 Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns (including joint, marginal, and conditional relative frequencies) to describe possible associations and trends in the data.

  • AI.DS.6 Understand that statistics and data are non-neutral and designed to serve a particular interest. Analyze the possibilities for whose interest might be served and how the representations might be misleading.